Structured Workflow
Enforces disciplined programming practices for AI assistants by requiring audit and verification of outputs at each development phase.
About
Structured Workflow is an innovative Model Context Protocol (MCP) server designed to overcome the common frustrations of AI skipping critical analysis in development. It enforces disciplined programming practices by requiring AI assistants to systematically inventory and audit their work and produce verified outputs at each development phase, preventing common issues like duplicated code or misaligned changes. Built out of a personal need, this server automates a structured approach, ensuring AI performs thorough analysis and planning before implementing changes, leading to more robust and integrated solutions.
Key Features
- Enforces progression through specific development phases (e.g., audit, analysis, planning, implementation).
- Validates outputs for meaningful content, proper JSON format, and phase-specific requirements.
- Supports various development workflows, including refactoring, feature development, and test-driven development.
- 2 GitHub stars
- Manages session state to track progress and prevent skipping phases.
- Requires mandatory, structured documentation or verified outputs at each phase.
Use Cases
- Enforcing disciplined, systematic AI-driven software development workflows.
- Automating structured refactoring processes to improve existing codebases.
- Guiding AI through test-driven development (TDD) cycles with enforced Red-Green-Refactor steps.
